Gestures may be viewed as an important aspect of body language and may be used every day in communications between people. For many people, it may be difficult to avoid making some kind of gesture when communicating face to face with another person. Gestures may convey messages easily and seemingly wordlessly. Doing able to consistently and rapidly assess and perform gestures may form the basis of many forms of entertainment, including games that can be either cooperative or competitive in nature. Gestures may represent a variety of different things including emotions to representations of more concrete things such as intentions, people, places or things. Finding a way to differentiate between these forms of communication accurately may be beneficial for a variety of purposes.
Typically in the industry, the challenges of implementing gesture recognition systems would be overcome by using shape descriptors in combination with various processes as evidenced in the works of Prof. Ling Guan and Prof. Matthew Kyan and the published papers “Computerized Recognition of Human Gestures” by A. Bulzacki, L. Zhao, L. Guan and K. Raahemifar and “An Introduction to Gesture Recognition Through Conversion to a Vector Based Medium” by A. Bulzacki, L. Chan and L. Zhao. However, despite the general direction taken by these leaders in the field and their suggestion to continue on this path, the inventor took a different approach to solving the gesture recognition problem as disclosed below.